Optical coherence tomography (OCT) is a safe and non-invasive imaging technique providing high axial resolution. A spectral-domain OCT scanner capable of acquiring volumetric data of the retina is becoming an increasingly important modality in ophthalmology for the diagnosis and management of a variety of retinal diseases such as glaucoma, diabetic retinopathy and age related macular degeneration (AMD) which are major causes of a loss of vision. To analyze and track these ocular diseases, developments of the automated methods for detecting intraretinal layers, optic discs and retinal blood vessels from spectral-domain OCT scans are highly required recently. The major contributions of this thesis include: 1) developing a fast method that can automatically segment ten intraretinal layers in the spectral-domain macular OCT scan for the layer thickness analysis, 2) developing a method that can automatically segment the optic disc cup and neuroretinal rim in the spectral-domain OCT scan centered at the optic nerve head (ONH) to measure the cup-to-disc ratio, an important structural indicator for the progression of glaucoma, and 3) developing a method that can automatically segment the 3-D retinal blood vessels in the spectral-domain ONH-centered OCT scan to extract 3-D features of the vessels for the diagnosis of retinal vascular diseases.